양형과 인공지능 - 국민의 법감정 수렴, 위험 판단, 양형 분석을 중심으로 -

Artificial intelligence technology is making remarkable progress. This emerging technology is anticipated to find applications in numerous facets of the judiciary's functions in the near future, notably in aiding judges in their tasks. In this article, we delve into three key domains where AI has the potential to be leveraged in sentencing, either now or in the near future. Firstly, the paper discusses diversification in the methods used to aggregate public sentiment concerning the criminal policy, facilitated by sentiment analysis. This is accomplished by gathering online posts and commentary about sentencing, which are then classified and analyzed using an AI tool known as sentiment analysis. This approach allows us to discern patterns in legal sentiment and gauge honest reactions that are elusive when traditional opinion gathering methods are employed. These conventional methods include public hearings, polls, and soliciting opinions from relevant organizations. Secondly, the article explores the objectification of risk assessment via recidivism risk prediction. We review various discussions happening in the United States, where AI tools for predicting recidivism risk are being deployed in the sentencing process. We further summarize the issues to be considered before introducing these tools in Korea. Lastly, we highlight the automation of sentencing analysis using information extraction technology. If the sentencing data analysts within the Sentencing Commission can automate the extraction of sentencing factors and the term of sentences from judicial decisions, a task traditionally performed manually, it would not only enable real-time analysis of sentencing, but also pave the way for delivering real-time sentencing statistics to judges.